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Interaction graph-based characterization of quantum benchmarks for improving quantum circuit mapping techniques
Published 13 Dec 2022 in quant-ph and cs.ET | (2212.06640v3)
Abstract: To execute quantum circuits on a quantum processor, they must be modified to meet the physical constraints of the quantum device. This process, called quantum circuit mapping, results in a gate/circuit depth overhead that depends on both the circuit properties and the hardware constraints, being the limited qubit connectivity a crucial restriction. In this paper, we propose to extend the characterization of quantum circuits by including qubit interaction graph properties using graph theory-based metrics in addition to previously used circuit-describing parameters. This approach allows for in-depth analysis and clustering of quantum circuits and a comparison of performance when run on different quantum processors, aiding in developing better mapping techniques. Our study reveals a correlation between interaction graph-based parameters and mapping performance metrics for various existing configurations of quantum devices. We also provide a comprehensive collection of quantum circuits and algorithms for benchmarking future compilation techniques and quantum devices.
- Li, G., Ding, Y., Xie, Y.: Tackling the qubit mapping problem for NISQ-era quantum devices. In: International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 1001–1014 (2019) (3) Murali, P., Baker, J.M., Javadi-Abhari, A., Chong, F.T., Martonosi, M.: Noise-adaptive compiler mappings for noisy intermediate-scale quantum computers. In: International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 1015–1029 (2019) (4) Tannu, S.S., Qureshi, M.K.: Not all qubits are created equal: A case for variability-aware policies for NISQ-era quantum computers. In: International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 987–999 (2019) (5) LI, G., Ding, Y., Xie, Y.: Towards efficient superconducting quantum processor architecture design. In: Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 1031–1045 (2020) (6) Zulehner, A., Paler, A., Wille, R.: An efficient methodology for mapping quantum circuits to the IBM QX architectures. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2018) (7) Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Baker, J.M., Javadi-Abhari, A., Chong, F.T., Martonosi, M.: Noise-adaptive compiler mappings for noisy intermediate-scale quantum computers. In: International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 1015–1029 (2019) (4) Tannu, S.S., Qureshi, M.K.: Not all qubits are created equal: A case for variability-aware policies for NISQ-era quantum computers. In: International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 987–999 (2019) (5) LI, G., Ding, Y., Xie, Y.: Towards efficient superconducting quantum processor architecture design. In: Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 1031–1045 (2020) (6) Zulehner, A., Paler, A., Wille, R.: An efficient methodology for mapping quantum circuits to the IBM QX architectures. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2018) (7) Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tannu, S.S., Qureshi, M.K.: Not all qubits are created equal: A case for variability-aware policies for NISQ-era quantum computers. In: International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 987–999 (2019) (5) LI, G., Ding, Y., Xie, Y.: Towards efficient superconducting quantum processor architecture design. In: Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 1031–1045 (2020) (6) Zulehner, A., Paler, A., Wille, R.: An efficient methodology for mapping quantum circuits to the IBM QX architectures. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2018) (7) Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com LI, G., Ding, Y., Xie, Y.: Towards efficient superconducting quantum processor architecture design. In: Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 1031–1045 (2020) (6) Zulehner, A., Paler, A., Wille, R.: An efficient methodology for mapping quantum circuits to the IBM QX architectures. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2018) (7) Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Zulehner, A., Paler, A., Wille, R.: An efficient methodology for mapping quantum circuits to the IBM QX architectures. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2018) (7) Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Murali, P., Baker, J.M., Javadi-Abhari, A., Chong, F.T., Martonosi, M.: Noise-adaptive compiler mappings for noisy intermediate-scale quantum computers. In: International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 1015–1029 (2019) (4) Tannu, S.S., Qureshi, M.K.: Not all qubits are created equal: A case for variability-aware policies for NISQ-era quantum computers. In: International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 987–999 (2019) (5) LI, G., Ding, Y., Xie, Y.: Towards efficient superconducting quantum processor architecture design. In: Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 1031–1045 (2020) (6) Zulehner, A., Paler, A., Wille, R.: An efficient methodology for mapping quantum circuits to the IBM QX architectures. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2018) (7) Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tannu, S.S., Qureshi, M.K.: Not all qubits are created equal: A case for variability-aware policies for NISQ-era quantum computers. In: International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 987–999 (2019) (5) LI, G., Ding, Y., Xie, Y.: Towards efficient superconducting quantum processor architecture design. In: Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 1031–1045 (2020) (6) Zulehner, A., Paler, A., Wille, R.: An efficient methodology for mapping quantum circuits to the IBM QX architectures. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2018) (7) Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com LI, G., Ding, Y., Xie, Y.: Towards efficient superconducting quantum processor architecture design. In: Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 1031–1045 (2020) (6) Zulehner, A., Paler, A., Wille, R.: An efficient methodology for mapping quantum circuits to the IBM QX architectures. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2018) (7) Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Zulehner, A., Paler, A., Wille, R.: An efficient methodology for mapping quantum circuits to the IBM QX architectures. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2018) (7) Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Tannu, S.S., Qureshi, M.K.: Not all qubits are created equal: A case for variability-aware policies for NISQ-era quantum computers. In: International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 987–999 (2019) (5) LI, G., Ding, Y., Xie, Y.: Towards efficient superconducting quantum processor architecture design. In: Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 1031–1045 (2020) (6) Zulehner, A., Paler, A., Wille, R.: An efficient methodology for mapping quantum circuits to the IBM QX architectures. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2018) (7) Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com LI, G., Ding, Y., Xie, Y.: Towards efficient superconducting quantum processor architecture design. In: Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 1031–1045 (2020) (6) Zulehner, A., Paler, A., Wille, R.: An efficient methodology for mapping quantum circuits to the IBM QX architectures. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2018) (7) Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Zulehner, A., Paler, A., Wille, R.: An efficient methodology for mapping quantum circuits to the IBM QX architectures. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2018) (7) Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- LI, G., Ding, Y., Xie, Y.: Towards efficient superconducting quantum processor architecture design. In: Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems, pp. 1031–1045 (2020) (6) Zulehner, A., Paler, A., Wille, R.: An efficient methodology for mapping quantum circuits to the IBM QX architectures. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2018) (7) Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Zulehner, A., Paler, A., Wille, R.: An efficient methodology for mapping quantum circuits to the IBM QX architectures. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2018) (7) Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Zulehner, A., Paler, A., Wille, R.: An efficient methodology for mapping quantum circuits to the IBM QX architectures. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2018) (7) Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Venturelli, D., Do, M., O’Gorman, B., Frank, J., Rieffel, E., Booth, K.E., Nguyen, T., Narayan, P., Nanda, S.: Quantum circuit compilation: An emerging application for automated reasoning (2019) (8) Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Lao, L., van Wee, B., Ashraf, I., van Someren, J., Khammassi, N., Bertels, K., Almudever, C.: Mapping of lattice surgery-based quantum circuits on surface code architectures. Quantum Science and Technology 4, 015005 (2019) (9) Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Lao, L., Manzano, D.M., van Someren, H., Ashraf, I., Almudever, C.G.: Mapping of quantum circuits onto nisq superconducting processors. arXiv preprint arXiv:1908.04226 (2019) (10) Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Herbert, S., Sengupta, A.: Using reinforcement learning to find efficient qubit routing policies for deployment in near-term quantum computers. arXiv:1812.11619 (2018) (11) Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Lye, A., Wille, R., Drechsler, R.: Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 178–183 (2015) (12) Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Lao, L., van Someren, H., Ashraf, I., Almudever, C.G.: Timing and resource-aware mapping of quantum circuits to superconducting processors. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (2021) (13) Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Lao, L., Browne, D.E.: 2QAN: A quantum compiler for 2-local qubit Hamiltonian simulation algorithms. arXiv (2021). https://doi.org/10.48550/ARXIV.2108.02099. https://arxiv.org/abs/2108.02099 (14) Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Li, G., Shi, Y., Javadi-Abhari, A.: Software-hardware co-optimization for computational chemistry on superconducting quantum processors. arXiv preprint arXiv:2105.07127 (2021) (15) Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Lao, L., Browne, D.: 2qan: A quantum compiler for 2-local qubit hamiltonian simulation algorithms. arXiv preprint arXiv:2108.02099 (2021) (16) Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Tomesh, T., Gokhale, P., Omole, V., Ravi, G.S., Smith, K.N., Viszlai, J., Wu, X.-C., Hardavellas, N., Martonosi, M.R., Chong, F.T.: Supermarq: A scalable quantum benchmark suite. In: 2022 IEEE International Symposium on High-Performance Computer Architecture (HPCA), pp. 587–603 (2022). IEEE (17) Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Resch, S., Karpuzcu, U.R.: Quantum computing: an overview across the system stack. arXiv preprint arXiv:1905.07240 (2019) (18) Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Bharti, K., Cervera-Lierta, A., Kyaw, T.H., Haug, T., Alperin-Lea, S., Anand, A., Degroote, M., Heimonen, H., Kottmann, J.S., Menke, T., Mok, W.-K., Sim, S., Kwek, L.-C., Aspuru-Guzik, A.: Noisy intermediate-scale quantum algorithms. Reviews of Modern Physics 94(1) (2022). https://doi.org/10.1103/revmodphys.94.015004 (19) et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- et al., M.S.A.: Qiskit: An Open-source Framework for Quantum Computing (2021). https://doi.org/10.5281/zenodo.2573505 (20) Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Li, A.: OpenQASM Benchmarks Collection. GitHub (2019) (21) Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Siraichi, M.Y., Santos, V.F.d., Collange, S., Pereira, F.M.Q.: Qubit allocation. In: International Symposium on Code Generation and Optimization, pp. 113–125 (2018) (22) Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Wille, R., Keszocze, O., Walter, M., Rohrs, P., Chattopadhyay, A., Drechsler, R.: Look-ahead schemes for nearest neighbor optimization of 1D and 2D quantum circuits. In: Asia and South Pacific Design Automation Conference, pp. 292–297 (2016) (23) Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Guerreschi, G.G., Park, J.: Two-step approach to scheduling quantum circuits. Quantum Science and Technology 3(4), 045003 (2018) (24) Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Dousti, M.J., Pedram, M.: Minimizing the latency of quantum circuits during mapping to the ion-trap circuit fabric. In: Design Automation and Test in Europe (2012) (25) Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Bahreini, T., Mohammadzadeh, N.: An MINLP model for scheduling and placement of quantum circuits with a heuristic solution approach. Journal on Emerhing Technologies in Computing 12(3), 29 (2015) (26) Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Venturelli, D., Do, M., Rieffel, E., Frank, J.: Compiling quantum circuits to realistic hardware architectures using temporal planners. Quantum Science and Technology 3(2), 025004 (2018) (27) Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Pozzi, M.G., Herbert, S.J., Sengupta, A., Mullins, R.D.: Using reinforcement learning to perform qubit routing in quantum compilers. arXiv preprint arXiv:2007.15957 (2020) (28) Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Guerreschi, G.G.: Scheduler of quantum circuits based on dynamical pattern improvement and its application to hardware design. arXiv:1912.00035 (2019) (29) Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Itoko, T., Raymond, R., Imamichi, T., Matsuo, A.: Optimization of quantum circuit mapping using gate transformation and commutation. Integration 70, 43–50 (2020) (30) Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Tan, B., Cong, J.: Optimal qubit mapping with simultaneous gate absorption. arXiv preprint arXiv:2109.06445 (2021) (31) Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Jiang, H., Deng, Y., Xu, M.: Quantum circuit transformation based on subgraph isomorphism and tabu search. arXiv preprint arXiv:2104.05214 (2021) (32) Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Li, S., Zhou, X., Feng, Y.: Qubit mapping based on subgraph isomorphism and filtered depth-limited search. IEEE Transactions on Computers (2020) (33) Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Bandic, M., Zarein, H., Alarcon, E., Almudever, C.G.: On structured design space exploration for mapping of quantum algorithms. In: 2020 XXXV Conference on Design of Circuits and Integrated Systems (DCIS), pp. 1–6 (2020). IEEE (34) Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Hillmich, S., Zulehner, A., Wille, R.: Exploiting quantum teleportation in quantum circuit mapping. In: 2021 26th Asia and South Pacific Design Automation Conference (ASP-DAC), pp. 792–797 (2021). IEEE (35) Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Blume-Kohout, R., Young, K.C.: A volumetric framework for quantum computer benchmarks. Quantum 4, 362 (2020) (36) Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Lubinski, T., Johri, S., Varosy, P., Coleman, J., Zhao, L., Necaise, J., Baldwin, C.H., Mayer, K., Proctor, T.: Application-oriented performance benchmarks for quantum computing. arXiv preprint arXiv:2110.03137 (2021) (37) Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Mills, D., Sivarajah, S., Scholten, T.L., Duncan, R.: Application-motivated, holistic benchmarking of a full quantum computing stack. arXiv preprint arXiv:2006.01273 (2020) (38) Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Steinberg, M.A., Feld, S., Almudever, C.G., Marthaler, M., Reiner, J.-M.: Topological-graph dependencies and scaling properties of a heuristic qubit-assignment algorithm. IEEE Transactions on Quantum Engineering 3, 1–14 (2022). https://doi.org/10.1109/TQE.2022.3160015 (39) A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- A Quadratic Unconstrained Binary Optimization Approach for Qubit Mapping. unpublished, Master Thesis (2023) (40) Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Baker, J.M., Duckering, C., Hoover, A., Chong, F.T.: Time-sliced quantum circuit partitioning for modular architectures. In: Proceedings of the 17th ACM International Conference on Computing Frontiers, pp. 98–107 (2020) (41) Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Bandic, M., Prielinger, L., Nüßlein, J., Ovide, A., Rodrigo, S., Abadal, S., van Someren, H., Vardoyan, G., Alarcon, E., Almudever, C.G., et al.: Mapping quantum circuits to modular architectures with qubo. arXiv preprint arXiv:2305.06687 (2023) (42) Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Hernández, J.M., Van Mieghem, P.: Classification of graph metrics. Delft University of Technology: Mekelweg, The Netherlands, 1–20 (2011) (43) Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Khammassi, N., Ashraf, I., Someren, J., Nane, R., Krol, A., Rol, M.A., Lao, L., Bertels, K., Almudever, C.G.: Openql: A portable quantum programming framework for quantum accelerators. ACM Journal on Emerging Technologies in Computing Systems (JETC) 18(1), 1–24 (2021) (44) Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Freedman, D., Pisani, R., Purves, R.: Statistics (international student edition). Pisani, R. Purves, 4th edn. WW Norton & Company, New York (2007) (45) Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Lloyd, S.: Least squares quantization in pcm. IEEE Transactions on Information Theory 28(2), 129–137 (1982). https://doi.org/10.1109/TIT.1982.1056489 (46) Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Rousseeuw, P.J.: Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics 20, 53–65 (1987) (47) qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- qbench benchmark suite. https://github.com/QE-Lab/qbench (2021) (48) Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Li, A., Krishnamoorthy, S.: Qasmbench: A low-level qasm benchmark suite for nisq evaluation and simulation. arXiv preprint arXiv:2005.13018 (2020) (49) UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- UCLA: QUEKO benchmark. UCLA (2020) (50) JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- JKU: Quantum Circuit Test Set (Zulehner). JKU (2018) (51) Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Möller, M., Schalkers, M.: : A cross-platform programming framework for quantum-accelerated scientific computing. In: International Conference on Computational Science, pp. 451–464 (2020). Springer (52) Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Valada, D.: OpenQl Random circuits. GitHub (2020) (53) Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Microsoft: Microsoft QDK. https://docs.microsoft.com/en-us/quantum/ (2020) (54) QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- QuTech: Python Quantum Inspire Benchmarks. GitHub (55) Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Developers, C.: Cirq. https://doi.org/10.5281/zenodo.6599601. See full list of authors on Github: https://github .com/quantumlib/Cirq/graphs/contributors. https://doi.org/10.5281/zenodo.6599601 (56) Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Smith, R.S., Curtis, M.J., Zeng, W.J.: A Practical Quantum Instruction Set Architecture (2016) (57) Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Sivarajah, S., Dilkes, S., Cowtan, A., Simmons, W., Edgington, A., Duncan, R.: t||||ket⟩⟩\rangle⟩: a retargetable compiler for NISQ devices. Quantum Science and Technology 6(1), 014003 (2020). https://doi.org/10.1088/2058-9565/ab8e92 (58) Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Cross, A.: The ibm q experience and qiskit open-source quantum computing software. In: APS March Meeting Abstracts, vol. 2018, pp. 58–003 (2018) (59) Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Last, T., Samkharadze, N., Eendebak, P., Versluis, R., Xue, X., Sammak, A., Brousse, D., Loh, K., Polinder, H., Scappucci, G., Veldhorst, M., Vandersypen, L., Maturová, K., Veltin, J., Alberts, G.: Quantum inspire - qutech’s platform for co-development and collaboration in quantum computing. In: Sanchez, M., Panning, E. (eds.) Novel Patterning Technologies for Semiconductors, MEMS/NEMS and MOEMS 2020. Proceedings of SPIE - The International Society for Optical Engineering, vol. 11324. SPIE, United States. https://doi.org/10.1117/12.2551853 (60) Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Wille, R., Große, D., Teuber, L., Dueck, G.W., Drechsler, R.: Revlib: An online resource for reversible functions and reversible circuits. In: 38th International Symposium on Multiple Valued Logic (ismvl 2008), pp. 220–225 (2008). IEEE (61) Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Nielsen, M.A., Chuang, I.: Quantum computation and quantum information. American Association of Physics Teachers (2002) (62) Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Cross, A.W., Bishop, L.S., Sheldon, S., Nation, P.D., Gambetta, J.M.: Validating quantum computers using randomized model circuits. Physical Review A 100(3), 032328 (2019) (63) Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Overwater, R.W., Babaie, M., Sebastiano, F.: Neural-network decoders for quantum error correction using surface codes: A space exploration of the hardware cost-performance tradeoffs. IEEE Transactions on Quantum Engineering 3, 1–19 (2022) (64) IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- IBM. https://www.ibm.com/. Accessed: 2022-11 (65) Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Rigetti. https://medium.com/rigetti/. Accessed: 2022-11 (66) Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Murali, P., Linke, N.M., Martonosi, M., Abhari, A.J., Nguyen, N.H., Alderete, C.H.: Full-stack, real-system quantum computer studies: Architectural comparisons and design insights. In: 2019 ACM/IEEE 46th Annual International Symposium on Computer Architecture (ISCA), pp. 527–540 (2019). IEEE (67) Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- Nishio, S., Pan, Y., Satoh, T., Amano, H., Meter, R.V.: Extracting success from ibm’s 20-qubit machines using error-aware compilation. ACM Journal on Emerging Technologies in Computing Systems (JETC) 16(3), 1–25 (2020) (68) QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
- QUTECH: Quantum inspire (2020). https://www.quantum-inspire.com
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